In biotechnology, flow cytometry involves the use of lasers and optics to perform cell counting, cell sorting, biomarker detection, and protein engineering. Cells are suspended in a stream of fluid and passed by an electronic detection apparatus, which can analyze the physical and chemical characteristics of the cells and/or other microscopic particles in the fluid. In some cases, fluorescent markers or labels having desired properties may be attached to target features on the cells in order to be used as a quantitative tool.
Modern flow cytometers are able to analyze several thousand particles every second in real-time in order to provide an automated quantification of parameters associated with those particles. Some flow cytometers may also be able to actively sort, separate, and isolate particles having specific properties in order to obtain particle populations of interest.
Flow cytometry is frequently used in the diagnosis of health disorders, as well as in basic research, clinical practice, and clinical trials. For instance, flow cytometry can be used to detect the presence of a specific particle (e.g., a pathogen) in a cell sample. However, in order for a flow cytometer to produce consistent and repeatable results (e.g., reliably identify that specific particle), the components of the flow cytometer may need to follow a set of rules or procedures specifically tailored to sorting, separating, and isolating that particular particle.
A set of these procedures may need to be devised, tested, and implemented into a usable form that can be interpreted by the flow cytometer in order to instruct the components of the flow cytometer to follow the set of procedures. Implementing the set of procedures may involve encapsulating the set of procedures into a programming language that can be interpreted by the flow cytometer. However, expressing the set of procedures in the programming language may be a difficult and time-consuming task, which involves having to learn the programming language to program the set of procedures. This implementation time would be in addition to the time also needed for devising and testing the set of procedures. As a result, the users of flow cytometry machines frequently do not have the time or capacity needed to create these sets of procedures and those tasks are often left to specialists.
Thus, there exists a need for a quicker and easier way to devise, test, and implement sets of procedures usable by a flow cytometry machine. This would improve the development time for these sets of procedures and could potentially improve the health outcomes of hundreds of thousands of people across the world, such as in the case of generating a set of procedures for reliably identifying a new pathogen for the purposes of diagnosis.